This project provides a bilingual Chinese-English translation of Antonio Gulli's "Agentic Design Patterns: A Hands-On Guide to Building Intelligent Systems." It aims to make the concepts and practical methods for designing modern AI agents accessible to a broader audience, including AI engineers, software architects, researchers, and students. The translated content includes explanations of core and advanced agent design patterns, accompanied by runnable code examples, offering a practical resource for building intelligent systems.

How It Works

This repository serves as a translated documentation effort for the book "Agentic Design Patterns." It meticulously translates the original English content into Chinese, presenting both languages side-by-side for clarity. Key concepts, design patterns (such as Prompt Chaining, Routing, Parallelization, Reflection, Tool Use, Planning, Memory Management, and Multi-Agent Collaboration), and practical code examples are rendered in Markdown, preserving original code links and highlighting Chinese text. The project focuses on accurately conveying the book's technical guidance on agent system architecture and implementation.

Quick Start & Requirements

To run the code examples:

• Clone the repository: git clone https://github.com/fzy2012/rhzl-Agentic-Design-Patterns-cn.git
• Navigate to the directory: cd rhzl-Agentic-Design-Patterns-cn
• Set up a Python virtual environment (recommended): python3 -m venv venv and activate it (source venv/bin/activate or venv\Scripts\activate).
• Install dependencies: pip install langchain langchain-community langchain-openai langgraph.
• Configure API Key: Create a .env file in the root directory with OPENAI_API_KEY=your-openai-api-key-here (or OpenRouter details).
• Run examples: Execute Python scripts from the codes/ directory (e.g., python codes/Chapter-01-Prompt-Chaining-Example.py).
• Online execution is available via Google Colab links provided within each code example file.
• Prerequisites include Python 3, Git, an OpenAI API key (or compatible), and network connectivity.

Highlighted Details

• Comprehensive bilingual (Chinese-English) translation of the book's content.
• Chinese text is highlighted using <mark> tags for easy visual distinction.
• All original code example links from the book are retained.
• Detailed translation progress is tracked per chapter, indicating AI translation, human review, and cross-review status.
• Practical code examples are provided for most chapters, facilitating hands-on learning.

Maintenance & Community

The project is maintained by the Ruhang365 team. Community contributions are welcomed for error reporting, translation improvements, and proofreading. Further AI learning resources and technical sharing are available via the "入行365" WeChat public account.

Licensing & Compatibility

The original book is copyrighted by Antonio Gulli and Springer, with royalties donated to Save the Children. The translated content is released under the CC BY-NC 4.0 license. This license permits free copying, distribution, display, and adaptation for non-commercial use only, provided attribution is given. Commercial use is strictly prohibited and requires explicit permission from the translators and original copyright holders.

Limitations & Caveats

The translation process is ongoing; several chapters are marked as "in progress" (⏳) or "not started" (❌) for human review and cross-review stages, indicating incomplete finalization. Some code examples may also be pending addition or full review. Crucially, the CC BY-NC 4.0 license imposes a strict non-commercial restriction on the use of the translated content, limiting its applicability for commercial projects or integration into proprietary systems without separate licensing agreements.